基于人工神经网络的沥青路面剩余寿命分析

路面整体结构性能评估是公路养护或重建决策优化的一项重要参考依据，一般情况下，如果路面的服务能力指数降到可接受水平以下，就有必要对当前整体性能(剩余寿命)进行评价，决定是否需要延长寿命或者进行重建设计，因此，利用人工神经网络(ANN)方法建立了沥青路面剩余寿命预测模型，由此程序可以由落锤弯沉仪(FWD)弯沉数据快速预估路面的剩余寿命，这种方法直观、准确，并且不需要反算模量，对于道路工作者的养护和补强罩面工作具有参考价值。

Analysis of Remaining Service Life for Asphalt Pavement Based on Artificial Neural Network

Assessing the overall structure aging of pavement is a crucial reference in optimizing the maintenance or rehabilitation strategies of the highway network. In general, if the serviceability index of a pavement falls below an acceptable level, the estimation of the current integrity of the pavement in terms of its remaining service life is desirable to support decisions, such as whether to extend the service life or to design and rebuild the section. Therefore, a prediction model of remaining service life for asphalt pavement was built based on artificial neural network. The remaining service life for asphalt pavement can be predicted rapidly and correctly according to FWD data, dispensing with modulus calculation. The model proposed may has great value in the daily work of maintenance or rehabilitation.